Source Free Domain Adaptation

Source-Free Domain Adaptation (SFDA) is a domain adaptation method in the field of machine learning and computer vision, aimed at adapting pre-trained models to a new target domain without access to source domain data. This approach has significant advantages in scenarios where source data cannot be shared due to privacy issues, large data volumes, or proprietary restrictions, effectively enhancing the model's generalization and performance in new environments.